A methodology for screening of microalgae as a decision making tool for energy and green chemical process applications

The increasing interest for biotechnological use of microalgae demands a methodology for selection of species suitable to support the development of technologies based on the use of such non-conventional renewable raw material, i.e., green industrial applications. The vast and expanding collection of experimental data on both cell growth and biomass composition available in the literature can be used to reduce the cost of the experimental investigations required to support process engineering and optimization. Selecting the appropriate organism requires extracting useful information from such data, a cumbersome task since various multidisciplinary factors must be considered. This paper presents a computer-aided methodology for selecting appropriate algal species given an energy or green chemical process application employing microalgae as a renewable raw material. The approach is “system oriented”, based on biomass composition and chemical processing of the biomass downstream of the CO₂ biofixation and harvesting operations. Quantitative performance results are supported by professional process simulation. Besides comparison of a set of species performances, the proposed methodology also allows the discrimination among distinct algal compositions resulting from different growth conditions for a given species. Furthermore, three categories of screening metrics are proposed to be maximized by the decision making procedure in order to elicit the relevant information. To demonstrate the potential of the proposed methodology, a databank of both biochemical and elemental compositions of microalgal biomass was used in three green applications: Assessment of biomass heating value; production of syngas by gasification of the biomass; and production of Bio-H₂. Within the accuracy of the databank employed to illustrate the procedure, the methodology selected Botryococcus braunii and Isochrysis galbana as potential promising candidates, for the three examined applications.     

Influence of mesostasis in volcanic rocks on the alkali-aggregate reaction

Mesostasis material present in the interstices of volcanic rocks is the main cause of the alkali-aggregate reaction (AAR) in concretes made with these rock aggregates. Mesostasis often is referred to as volcanic glass, because it has amorphous features when analyzed by optical microscopy. However, this study demonstrates that mesostasis in the interstitials of volcanic rocks most often consists of micro to cryptocrystalline mineral phases of quartz, feldspars, and clays. Mesostasis has been identified as having different characteristics, and, thus, this new characterization calls for a re-evaluation of their influence on the reactivity of the volcanic rocks. The main purpose of this study is to correlate the characteristics of mesostasis with the AAR in mortar bars containing basalts and rhyolites.     

Short‐term load forecasting based on support vector regression and load profiling

The article proposes a methodology to forecast the electric load for the 24 h of the following day based on support vector regression. The study considers 24 distinct models, one for each predicted hour, where each individual model is treated independently. Its objective is to find the optimal combination of support vector machine parameters that could generalize low forecasting errors, using simulated annealing as a metaheuristic. The adopted methodology is compared to concurrent methods based on neural networks when applied to a simulated load diagram (to illustrate a distribution feeder supplying a sample of 740 consumers). The results have proven its effectiveness with mean absolute percentage errors being less than 5% for testing samples. The study also focuses on evaluating the potential benefits of adopting load profiling information as input in support vector regression, giving a consistent proof of its importance. Copyright © 2013 John Wiley & Sons, Ltd.     

Extraction and characterization of highly purified collagen from bovine pericardium for potential bioengineering applications

Bovine pericardium is widely used as a raw material in bioengineering as a source of collagen, a fundamental structural molecule. The physical, chemical, and biocompatibility characteristics of these natural fibers enable their broad use in several areas of the health sciences. For these applications, it is important to obtain collagen of the highest possible purity. The lack of a method to produce these pure biocompatible materials using simple and economically feasible techniques presents a major challenge to their production on an industrial scale. This study aimed to extract, purify, and characterize the type I collagen protein originating from bovine pericardium, considered to be an abundant tissue resource. The pericardium tissue was collected from male animals at slaughter age. Pieces of bovine pericardium were enzymatically digested, followed by a novel protocol developed for protein purification using ion-exchange chromatography. The material was extensively characterized by electrophoresis, scanning electron microscopy, energy dispersive X-ray spectroscopy, and infrared spectroscopy. The results showed a purified material with morphological properties and chemical functionalities compatible with type I collagen and similar to a highly purified commercial collagen. Thus, an innovative and relatively simple processing method was developed to extract and purify type I collagen from bovine tissue with potential applications as a biomaterial for regenerative tissue engineering.     

Influence of grape composition and winemaking on the anthocyanin composition of red wines of Tannat

The anthocyanin composition of Tannat red wines obtained with four winemaking techniques was evaluated in different years. The wines were elaborated with traditional maceration (TM), cold pre‐fermentative maceration, delayed extraction of anthocyanins and extended maceration. Two vinifications were carried out for each technique, employing 70 kg of grapes in each one. The anthocyanin composition of wines was analysed by high‐performance liquid chromatography–diode array detection. The results confirm the fundamental role of the grape composition on the anthocyanin composition of the wines. The winemaking had an important effect on the total concentration of anthocyanins and also may modify the anthocyanic profile of wines. The wines obtained with TM had higher or similar content of anthocyanins than those elaborated with the other techniques. Canonical discriminant analysis of data showed that vintage has a greater effect on anthocyanin concentration than winemaking techniques.     

Effects of supplemental progesterone after artificial insemination on expression of interferon-stimulated genes and fertility in dairy cows

The objectives of the current study were to evaluate the effects of supplemental progesterone after artificial insemination (AI) on expression of IFN-stimulated genes (ISG) in blood leukocytes and fertility in lactating dairy cows. Weekly cohorts of Holstein cows were blocked by parity (575 primiparous and 923 multiparous) and method of insemination (timed AI or AI on estrus) and allocated randomly within each block to untreated controls, a controlled internal drug release (CIDR) containing 1.38 g of progesterone from d 4 to 18 after AI (CIDR4), or a CIDR on d 4 and another on d 7 after AI and both removed on d 18 (CIDR4+7). Blood was sampled to quantify progesterone concentrations in plasma and mRNA expression in leukocytes for the ubiquitin-like IFN-stimulated gene 15-kDa protein (ISG15) and receptor transporter protein-4 (RTP4) genes. Pregnancy was diagnosed on d 34 ± 3 and 62 ± 3 after AI. Treatment increased progesterone concentrations between d 5 and 18 after AI in a dose-dependent manner (control = 3.42, CIDR4 = 4.97, and CIDR4+7 = 5.46 ng/mL). Cows supplemented with progesterone tended to have increased luteolysis by d 19 after AI (control = 17.2; CIDR4 = 29.1; CIDR4+7 = 30.2%), which resulted in a shorter AI interval for those reinseminated after study d 18. Pregnancy upregulated expression of ISG in leukocytes on d 19 of gestation, but supplementing progesterone did not increase mRNA abundance for ISG15 and RTP4 on d 16 after insemination and tended to reduce mRNA expression on d 19 after AI. For RTP4 on d 19, the negative effect of supplemental progesterone was observed only in the nonpregnant cows. No overall effect of treatment was observed on pregnancy per AI on d 62 after insemination and averaged 28.6, 32.7, and 29.5% for control, CIDR4, and CIDR4+7, respectively. Interestingly, an interaction between level of supplemental progesterone and method of AI was observed for pregnancy per AI. For cows receiving exogenous progesterone, the lower supplementation with CIDR4 increased pregnancy per AI on d 62 in cows inseminated following timed AI (CIDR4 = 39.2; CIDR4+7 = 27.5%); in those inseminated following detection of estrus, however, the use of a second insert on d 7 resulted in greater pregnancy per AI (CIDR4 = 26.9; CIDR4+7 = 31.5%). Pregnancy loss did not differ among treatments. Supplemental progesterone post-AI using a single intravaginal insert on d 4 was beneficial to pregnancy in cows inseminated following timed AI, but incremental progesterone with a second insert on d 7 did not improve fertility of dairy cows.     

Analysis of the mathematical model of the gas bubbling curtain injection on the bottom and the walls of a continuous casting tundish

In the present work, the behaviour of a gas bubbling curtain (GBC) in the continuous casting tundish of industry is studied by using a physical model in the scale of 1:3. This study was made with the following configurations of gas injection inside the tundish: no gas injection, gas injection on the bottom and combined gas injection (CGI) on the bottom and the walls. Mathematical simulations were performed using the Eulerian approach. Mathematical modelling was also used to determine the residence time distribution curves (RTD curves). For the validation of the mathematical model, experiments were made using the physical models to obtain the homogenisation time of salt solutions. All of the results were validated by the experimental results of the RTD curves. The plug flow fraction remained almost constant when gas injection was used on the walls, however the mean residence time and the dead volume fraction, increased and decreased, respectively. The CGI on the bottom and walls allowed the entire cross-section to be covered with the GBC which acted as a barrier to the passage of inclusions.     

Evaluation of the effect of heat input in superduplex stainless steel deposition by the plasma powder process*

Plasma powder surfacing is one of the latest processes for application of coatings, with control of dilution as its main feature. Surfacing with superduplex stainless steels is an interesting option for the construction and repair of equipment for applications in a highly corrosive environment, allowing the desired characteristics to be achieved: corrosion resistance and good mechanical properties. The aim of this work is to assess the ferrite content in the weld metal and the mechanical characteristics via microhardness profiles in surfacing of C-Mn steel pipes with deposition of UNS S32760 by plasma powder surfacing. Welding operations were carried out on pipes with deposition of SDSS, employing three welding heat input levels, varying the welding speed or the welding current. Then the geometry was analysed, the ferrite content in the weld metal was quantified and the microhardness profile was recorded. Variation in welding heat input caused changes in weld bead geometry, with variation in the welding current producing the most significant changes. Increase in heat input caused decrease in ferrite content of the weld metal. Regarding microhardness, only the condition with a higher level of welding current gave sufficiently high levels of microhardness in the weld metal.